A flexible uncertainty quantification method for linearly coupled multi-physics systems
Creators
Description
Highlights: •We propose a "modularly hybrid" UQ methodology suitable for independent development of module-based multi-physics simulation. •Our algorithmic framework allows for each module to have its own UQ method (either intrusive or non-intrusive). •Information from each module is combined systematically to propagate "global uncertainty". •Our proposed approach can allow for easy swapping of new methods for any modules without the need to address incompatibilities. •We demonstrate the proposed framework on a practical application involving a multi-species reactive transport model. -- Abstract: This paper presents a novel approach to building an integrated uncertainty quantification (UQ) methodology suitable for modern-day component-based approach for multi-physics simulation development. Our "hybrid" UQ methodology supports independent development of the most suitable UQ method, intrusive or non-intrusive, for each physics module by providing an algorithmic framework to couple these "stochastic" modules for propagating "global" uncertainties. We address algorithmic and computational issues associated with the construction of this hybrid framework. We demonstrate the utility of such a framework on a practical application involving a linearly coupled multi-species reactive transport model
Availability note (English)
Available from http://dx.doi.org/10.1016/j.jcp.2013.04.009Additional details
Identifiers
- DOI
- 10.1016/j.jcp.2013.04.009;
- PII
- S0021-9991(13)00258-1;
Publishing Information
- Journal Title
- Journal of Computational Physics
- Journal Volume
- 248
- Journal Page Range
- p. 383-401
- ISSN
- 0021-9991
- CODEN
- JCTPAH
INIS
- Country of Publication
- United States
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 45051873
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING;
- Descriptors DEI
- CHAOS THEORY; ELECTRIC UTILITIES; GAS UTILITIES; POLYNOMIALS; SIMULATION; STOCHASTIC PROCESSES; TRANSPORT THEORY
- Descriptors DEC
- FUNCTIONS; MATHEMATICS; PUBLIC UTILITIES
Optional Information
- Copyright
- Copyright (c) 2013 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.